{"title":"Parallelizing datalog: function symbols make a difference","authors":"Jürgen Seib","doi":"10.1109/PDIS.1991.183072","DOIUrl":null,"url":null,"abstract":"A Datalog program consists of function-free Horn clause rules. There are, however, some situations described more easily and more naturally by the use of general terms as arguments. A term is built up from variables, constants, and function symbols. A set of rules where the rules may contain function symbols is called a Datalog/sup Fun/ program. The paper discusses parallel processing of decomposable Datalog/sup Fun/ programs to overcome the performance problem. A decomposable program can be evaluated in parallel such that neither a communication nor a synchronization of the processors has to be established. The author and G. Lausen (1991) proposed the concept of generalized pivoting as a sufficient condition for decomposability of arbitrary but function-free Datalog programs. The current paper extends the concept of generalized pivoting to programs which may contain function symbols.<<ETX>>","PeriodicalId":210800,"journal":{"name":"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDIS.1991.183072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A Datalog program consists of function-free Horn clause rules. There are, however, some situations described more easily and more naturally by the use of general terms as arguments. A term is built up from variables, constants, and function symbols. A set of rules where the rules may contain function symbols is called a Datalog/sup Fun/ program. The paper discusses parallel processing of decomposable Datalog/sup Fun/ programs to overcome the performance problem. A decomposable program can be evaluated in parallel such that neither a communication nor a synchronization of the processors has to be established. The author and G. Lausen (1991) proposed the concept of generalized pivoting as a sufficient condition for decomposability of arbitrary but function-free Datalog programs. The current paper extends the concept of generalized pivoting to programs which may contain function symbols.<>